Abstract

A subclinical inflammatory reaction has been shown to precede the onset of type 2 (non-insulin-dependent) diabetes. We therefore
examined prospectively the effects of the central inflammatory cytokines interleukin (IL)-1β, IL-6, and tumor necrosis factor-α
(TNF-α) on the development of type 2 diabetes. We designed a nested case-control study within the prospective population-based
European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study including 27,548 individuals. Case subjects
were defined to be those who were free of type 2 diabetes at baseline and subsequently developed type 2 diabetes during a
2.3-year follow-up period. A total of 192 cases of incident type 2 diabetes were identified and matched with 384 non-disease-developing
control subjects. IL-6 and TNF-α levels were found to be elevated in participants with incident type 2 diabetes, whereas IL-1β
plasma levels did not differ between the groups. Analysis of single cytokines revealed IL-6 as an independent predictor of
type 2 diabetes after adjustment for age, sex, BMI, waist-to-hip ratio (WHR), sports, smoking status, educational attainment,
alcohol consumption, and HbA1c (4th vs. the 1st quartile: odds ratio [OR] 2.6, 95% CI 1.2–5.5). The association between TNF-α and future type 2 diabetes
was no longer significant after adjustment for BMI or WHR. Interestingly, combined analysis of the cytokines revealed a significant
interaction between IL-1β and IL-6. In the fully adjusted model, participants with detectable levels of IL-1β and elevated
levels of IL-6 had an independently increased risk to develop type 2 diabetes (3.3, 1.7–6.8), whereas individuals with increased
concentrations of IL-6 but undetectable levels of IL-1β had no significantly increased risk, both compared with the low-level
reference group. These results were confirmed in an analysis including only individuals with HbA1c <5.8% at baseline. Our data suggest that the pattern of circulating inflammatory cytokines modifies the risk for type 2 diabetes.
In particular, a combined elevation of IL-1β and IL-6, rather than the isolated elevation of IL-6 alone, independently increases
the risk of type 2 diabetes. These data strongly support the hypothesis that a subclinical inflammatory reaction has a role
in the pathogenesis of type 2 diabetes.

Low physical activity and hyperalimentation are lifestyle factors associated with an increased risk of type 2 diabetes (1). Despite more than 100 million patients affected worldwide and a dramatic socioeconomic burden due to vascular complications,
the etiology of type 2 diabetes is not yet completely understood.

It has been hypothesized that type 2 diabetes is a manifestation of an ongoing acute-phase response that is primarily characterized
by alterations of the so-called acute-phase proteins, such as C-reactive protein (CRP) (2,3). Cross-sectional and prospective studies demonstrated increased concentrations of markers of the acute-phase response (including
CRP, serum amyloid-A, and sialic acid) in patients with type 2 diabetes (2–14). In one of these studies, elevated levels of IL-6, which is known to be a main stimulator of the production of most acute-phase
proteins (10,11), were shown to increase the risk of diabetes (9). However, in addition to IL-6, other cytokines, such as interleukin (IL)-1β or tumor necrosis factor-α (TNF-α), are central
mediators of inflammatory reactions. It is well known that cytokines operate as a network in stimulating the production of
acute-phase proteins. For example, the effects of IL-6 on CRP synthesis largely depend on an interaction with IL-1β (11). The acute-phase response in various artificial inflammatory models requires both IL-6 and IL-1β, as demonstrated in the
respective knockout mouse models (12,13). These data strongly suggest that inflammatory reactions do not depend on single mediators, but rather that the pattern
of various cytokines is crucially important for the perpetuation of an acute-phase response.

Until now, there has been neither prospective evidence concerning the individual regulation of the inflammatory cytokines
IL-1β or TNF-α nor prospective evidence about the combined role of IL-1β, IL-6, and TNF-α preceding type 2 diabetes, although
the combined effects of these cytokines are likely to be more important than the circulating levels of the single cytokines.
We therefore designed a nested case-control study within the prospective population-based European Prospective Investigation
into Cancer and Nutrition (EPIC)-Potsdam cohort of 27,548 individuals to further evaluate the role of CRP, IL-1β, IL-6, and
TNF-α in the development of type 2 diabetes.

RESEARCH DESIGN AND METHODS

Study population.

The EPIC-Potsdam study, as part of the multicenter population-based cohort study EPIC, aims to explore the relation between
dietary and lifestyle factors and the development of complex diseases. Details of the recruitment procedure of EPIC-Potsdam
have been published (14). In brief, 27,548 subjects (women aged 35–65 years and men aged 40–65 years) were recruited from the general population.
Baseline examinations, including anthropometric measurements, blood sampling, a self-administered food frequency questionnaire,
and a personal interview on lifestyle habits and medical history were conducted between 1994 and 1998. Follow-up questionnaires
are sent to the study participants every 2–3 years to obtain information on, among other things, current medication and newly
developed diseases, including diabetes.

Anthropometry and lifestyle characteristics.

Anthropometric measurements (body height and weight, waist and hip circumference) were performed by trained personnel, with
the participants wearing only light underwear and without shoes (15). BMI was calculated as body weight (in kilograms) divided by body height (in meters) squared. Waist-to-hip ratio (WHR) was
calculated as waist divided by hip circumference.

Information on lifestyle characteristics were obtained from self-administered questionnaires and a personal, computer-guided
interview by trained and quality-monitored personnel (16). Sporting activities (hours per week) were calculated as the average of hours of sports per week during the summer and the
winter season.

End points and disease status.

We studied 27,548 participants of the population-based EPIC-Potsdam study. The follow-up procedure was successful in receiving
completely filled-in questionnaires from 96% of all cohort participants attending the baseline examination (17).

Case subjects were those who were free of type 2 diabetes at baseline and developed type 2 diabetes during the first 2- to
3-year follow-up, depending on the time of recruitment. Potential cases of incident diabetes were identified from self-reports
on incident disease, current medications, and/or current dietary treatment for diabetes (n = 399). For each potentially incident subject, a special questionnaire was sent to the primary care physician. The study
subject was considered as a case subject only if the diagnosis of newly developed diabetes was confirmed by this physician.
A total of 201 cases of incident diabetes were identified by this verification process until 1 November 2001. At that time,
another 10 potential incident cases were pending confirmation by the primary care physician. These subjects were not further
considered. The biochemical analysis regarding diabetes-associated antibodies GAD65 and IA-2 revealed that nine of the case
subjects should be considered as case subjects with type 1 diabetes, leaving 192 medically confirmed cases of type 2 diabetes.
Each of the 192 individuals with confirmed type 2 diabetes was matched with two control subjects by age (±1 year) and sex
(n = 384). For statistical analysis, those individuals with missing values in one of the variables being used in the statistical
models were not considered (n = 4 for case subjects, n = 7 for control subjects), thus leaving 188 case subjects and 377 control subjects for the final analysis.

Laboratory procedures.

Peripheral venous citrate-blood samples were taken at enrollment into the study. The blood samples were centrifuged at 1,000g for 10 min at 4°C. Plasma was then removed and stored in aliquots in freezers at −80°C until assays of the markers of interest
were performed. IL-1β, IL-6, and TNF-α were measured by enzyme-linked immunosorbent assays (ELISAs; R&D Systems, Minneapolis,
MN). CRP was determined by high-sensitivity ELISA (Immun Diagnostik, Bensheim, Germany). All assay procedures were performed
as described by the manufacturer. Blood samples were analyzed in random order to exclude systemic bias due to interassay variation.
Control specimens were analyzed simultaneously on each plate for every marker. The intra-assay coefficient of variation (CV)
ranged between 6.4 and 10.2% for IL-1β, 3.8 and 11.1% for IL-6, 8.7 and 14.8% for TNF-α, and 4.9 and 6.2% for CRP. The interassay
CV was 10.3% for IL-1β, 9.9% for IL-6, 16.1% for TNF-α, and 13.2% for CRP. The limits of detection were 0.1 pg/ml for IL-1β,
0.094 pg/ml for IL-6, 0.12 pg/ml for TNF-α, and 0.124 ng/ml for CRP. HbA1c was determined by enzyme immunoassay (DAKO Diagnostika, Hamburg, Germany). The intra-assay CV ranged from 2 to 3%, and the
interassay CV was 1.9%. Values of subjects without diabetes have been shown to range from 4.8 to 6.9% in this assay, according
to the information of the manufacturer. Diabetes-associated antibodies GAD65 and IA-2 were analyzed by radioimmunoassay (Medipan
Diagnostica, Selchow, Germany), which was performed as described by the manufacturer.

Statistical analyses.

For all analyses, we used SAS software release 8.0 (SAS Institute, Cary, NC). In a first step, measurement values of the laboratory
parameters (IL-1β, TNF-α, and CRP) below the limit of quantification (LOQ) were set at 0.7 × the respective LOQ (18). Means, standard deviations, and proportions of baseline characteristics of case and control subjects were calculated. The
means ± SD are reported. Significance was considered at two-tailed α < 0.05.

The nonparametric Wilcoxon’s rank-sum test was used to test for differences in continuous variables between case and control
subjects, and a χ2 test with 1 degree of freedom (Mantel-Haenszel test) was used to describe differences in proportions between case and control
subjects. Spearman correlation coefficients were used to test the association between anthropometric, lifestyle variables,
and cytokines.

Associations were initially investigated separately for IL-1β, IL-6, and TNF-α. IL-6 and TNF-α were divided into quartiles,
and CRP was dichotomized. Because of the high numbers of undetectable values, IL-1β was dichotomized. Because of case and
control exclusions due to missing values, primarily unconditional logistic regression analysis was used to estimate odds ratios
(ORs) and corresponding 95% CIs. As previously demonstrated, the estimation of the OR approximates the relative risk given
an infrequent disease occurrence (19). We therefore calculated the OR to estimate the relative risk to develop type 2 diabetes that is associated with increasing
categories of the investigated cytokine. Because the design of the study also allows conditional logistic analysis, study
results were recalculated using conditional logistic regression analysis. In the article, the results of the unconditional
regression and major results of the conditional regression analysis are shown. Estimates of relative risk were first obtained
from age-adjusted (continuous) and sex-adjusted (categorical: female and male) analyses; this analysis was followed by further
adjustment for BMI (continuous). The subsequent model also considers sex-normalized WHR (continuous), sporting activities
in hours/week (continuous), smoking status (categorical: current smoker and nonsmoker), alcohol consumption in grams/day (continuous),
and educational attainment (categorical: basic training, technical school, and university). In the last model, we additionally
added HbA1c (continuous) to the fully adjusted model to reduce potential bias caused by undetected cases of prevalent diabetes.

To investigate the role of cytokine patterns, formal interaction terms including the cytokines in question were analyzed.
Product terms were built from dichotomized subgroups. IL-1β was therefore dichotomized as previously described (setting individuals
with undetectable levels as 0 and those with detectable levels as 1), whereas IL-6 and TNF-α were dichotomized by using the
75th percentile as the cutoff point (setting individuals who were <75th percentile for both IL-6 and TNF-α as 0 and those
who were >75th quartile as 1). Quartile cut points were estimated from the combined group of control and case subjects. In
addition, ORs and 95% CIs were estimated for each combination, including two of these cytokines with the low-level category
(<75th percentile for IL-6 and TNF-α and nondetectable values of IL-1β, respectively) as the reference category.

To reduce bias by individuals with undetected prevalent type 2 diabetes at baseline, we repeated the analysis, including only
those case and control subjects with HbA1c <5.8%.

RESULTS

Clinical parameters.

Baseline characteristics of the participants are shown in Table 1. As expected, case subjects had higher BMI and WHR, and they exercised less (Table 1). Elevated glucose levels, such as impaired fasting glucose or impaired glucose tolerance, are well known to be a risk factor
for future type 2 diabetes (20), which is reflected in our study group by significantly elevated HbA1c levels in case subjects (6.39 ± 2.16%) compared with control subjects (4.73 ± 0.74%). Of the participants, 2.8% had undetectable
levels of CRP (5% for TNF-α and 62% for IL-1β, respectively). IL-6 levels were detectable in all participants. As demonstrated
in previous studies (8,9), elevated levels of CRP were found to be associated with an increased risk of type 2 diabetes in the fully adjusted model
(OR 1.9, 95% CI 1.2–3.2). With respect to clinical parameters and CRP, subgroup analysis (HbA1c <5.8%) yielded results comparable to the analysis that included all participants. For example, the risk of individuals with
elevated CRP levels to develop type 2 diabetes was 2.1 (95% CI 1.2–3.7) in the fully adjusted model in this subgroup. The
mean HbA1c was 4.5 ± 0.5% for control and 4.9 ± 0.5% for case subjects (P < 0.001) within the restricted subcohort. Correlations of cytokines, CRP, BMI, WHR, and HbA1c are demonstrated in Table 2.

Effects of single cytokines on diabetes risk

IL-6 independently predicts the risk of type 2 diabetes.

Mean baseline levels of IL-6 were higher among case subjects compared with control subjects (P < 0.0001). Elevated levels of IL-6 were associated with an increased risk of type 2 diabetes (risk estimates of individuals
according to IL-6 quartiles are demonstrated in Table 3). After adjustment for all covariables (BMI, WHR, sports, age, sex, smoking status, educational attainment, alcohol consumption,
and HbA1c), IL-6 was found to be an independent predictor of type 2 diabetes (OR 2.57, 95% CI 1.24–5.47) This result was confirmed
in conditional regression analysis (2.6, 1.2–5.9). Comparable and significant results were observed in analyses restricted
to case subjects with HbA1c <5.8% only. Within this subgroup analysis, the risk of individuals within the 4th quartile of IL-6 was also substantially
increased (3.1, 1.3–7.4 [unconditional]; 3.7, 1.16–11.9 [conditional]) in the fully adjusted model.

Elevated levels of TNF-α and IL-1β alone are not independently associated with future type 2 diabetes.

Mean concentrations of TNF-α were higher in case subjects (2.04 ± 1.51 pg/ml) compared with control subjects (1.79 ± 1.28
pg/ml, P < 0.01). The risk of type 2 diabetes increased with increasing quartiles of TNF-α (Table 3). However, after adjustment for BMI or WHR, this association was no longer significant. Correlation analysis showed a mild
correlation between TNF-α and BMI (r = 0.17, P < 0.001) or WHR (r = 0.15, P < 0.001). Again, analysis of participants with HbA1c <5.8% yielded a similar picture as analysis of all participants. For example, the ORs in the fully adjusted model including
HbA1c were 1.0, 1.8 (95% CI 0.8–3.8), 0.9 (0.4–1.9), and 1.3 (0.6–3.1) for the increasing quartiles. Using conditional regression
analysis also yielded no significant results regarding TNF-α–dependent relative risks after adjustment for BMI and/or WHR.

We found that 41.0% of case subjects and 36.6% of control subjects had detectable levels of IL-1β, which was not a statistically
significant difference. According to these data, the relative risk of developing type 2 diabetes was not associated with circulating
levels of IL-1β, independent of the model or type of analysis applied (Table 3).

Participants with a combined elevation of IL-6 levels and detectable levels of IL-1β were found to have an increased risk
of future type 2 diabetes (OR 3.3, 95% CI 1.7–6.8 [unconditional]; 3.479, 1.078–11.222 [conditional]) compared with the low-level
reference group in the fully adjusted model. In contrast, individuals with elevated levels of IL-6 but nondetectable levels
of IL-1β had no significantly increased risk to develop type 2 diabetes (1.2, 0.6–2.5 [unconditional]; 1.5, 0.5–4.4 [conditional])
compared with the low-level reference group in the fully adjusted model. These results were confirmed by the inclusion of
a formal interaction term between detectable IL-1β and elevated IL-6; this term was 3.3 (95% CI 1.1–9.7) and was significant
(Table 4). Similar results were obtained including only individuals with HbA1c <5.8%; here, the interaction term was 2.3 (1.1–5.1).

In crude analysis, individuals with a combined elevation of IL-6 and TNF-α or with a combined elevation of TNF-α and IL-1β
had a substantially increased risk compared with individuals with elevated levels of IL-6 alone or compared with the low-level
reference group. These effects of a combined elevation of IL-6 and TNF-α (OR 3.2, 95% CI 1.6–6.4) or IL-1β and TNF-α (2.3,
1.1–4.9) was still significant in the analysis restricted to participants with HbA1c <5.8%. However, as described for TNF-α alone, this effect did not remain significant in the fully adjusted model. Results
were again confirmed using conditional regression analysis and by calculation of formal interaction terms (Table 4).

DISCUSSION

We evaluated the effects of various inflammatory cytokines on the risk of type 2 diabetes. Participants with a combined elevation
of IL-6 and IL-1β had a roughly threefold increased risk of developing type 2 diabetes compared with the low-level reference
group. In contrast, participants with elevated levels of IL-6 alone (and undetectable levels of IL-1β) had no substantial
increase of their diabetes risk. In this regard, IL-1β appears to have a permissive role in the IL-6–mediated acute-phase
response preceding the onset of type 2 diabetes. Elevated levels of TNF-α were associated with an increased diabetes risk
in the crude analysis. However, this TNF-α-dependent effect was no longer significant after adjustment for BMI or WHR. Furthermore,
we found no significant effects of TNF-α on IL-1β- or IL-6-dependent risk estimates.

To the best of our knowledge, this is the first study to describe the combined effects of the three inflammatory cytokines
IL-1β, IL-6, and TNF-α on the risk to develop type 2 diabetes. However, some limitations of this study need to be considered.
It is well known that there is a relatively high proportion of individuals with undiagnosed type 2 diabetes among the general
population (21,22). We therefore adjusted for blood glucose control by including HbA1c into the fully adjusted model. To reduce the remaining potential bias of prevalent diabetes in case or control subjects at
baseline, we also performed separate analyses among participants (case and control subjects) with HbA1c <5.8%. A total of 94 individuals in our cohort provided fasting blood specimens. Within this subgroup, all case individuals
with HbA1c <5.8% had a baseline fasting glucose <7.0 mmol/l, which is sufficient to exclude diabetes in epidemiological studies, according
to American Diabetes Association criteria. Thus, the number of individuals with prevalent diabetes at baseline (in case and
control subjects) appears to be small in the analyses restricted to individuals with HbA1c <5.8%. However, physician-diagnosed cases (as in this study) are likely to represent more progressed stages of diabetes compared
with those diagnosed, for example, by an oral glucose tolerance test. Given that cytokine changes at baseline may be associated
with the stage of diabetes, one might expect weaker associations if earlier stages of diabetes are investigated. In addition,
some of the control subjects may have developed diabetes by the end of follow-up but were not diagnosed by a physician.

The robustness of results was additionally confirmed by inclusion of further covariates (preexisting hypertension and hyperlipidemia)
into the model, although there is no clear functional evidence that these factors influence the development of type 2 diabetes.
It is important to note that all of these additional analyses confirmed the findings described. Although BMI and WHR are more
common clinical measures of obesity and central obesity, respectively, they may not fully account for the metabolic consequences
of obesity and residual confounding even though adjustment for these parameters may exist. We analyzed various components
of the metabolic syndrome, and cytokine effects were found to be independent of hypertension or hyperlipidemia. Although previous
studies demonstrated that inflammatory markers are associated with future type 2 diabetes, even after adjustment for fasting
insulin (6,8), it remains to be elucidated whether this holds true for the cytokine changes described here. Another potential bias may
result from different precision of cytokine measurement. When two or more cytokines are entered into the statistical models,
the relative strength of association between cytokines and disease can be expected to be highest for the cytokine with the
least measurement error. In our study, inter- and intra-assay coefficients of variation were comparable in measurements of
the three cytokines. However, additional sources of measurement variability (related to venipuncture, blood processing, or
effects of long-term storage) may have differed for the three cytokines. Thus, we cannot entirely exclude that some of the
above-mentioned limitations may have influenced our results.

Our data suggest that the pattern of inflammatory cytokines is important in the pathogenesis of type 2 diabetes. These findings
are in line with the fact that inflammatory reactions depend on a cluster of cytokines rather than on single cytokines only.
Patterns of cytokine production differ with different inflammatory conditions, and cytokines are components of a large complex
signaling network (11–13). Several mechanisms, such as considerable influence of cytokines on lipid metabolism, may be important for the effects of
combined elevations of different cytokines. For example, both IL-6 and IL-1β act on the liver to produce the characteristic
dyslipidemia of the metabolic syndrome, with increased VLDL and decreased HDL (3). Combined elevation of IL-6 and IL-1β dramatically increased the expression of the acute-phase proteins, compared with the
effect of each cytokine alone (11). Another potential molecular mechanism how inflammation may be involved in the pathogenesis of type 2 diabetes has been
elucidated in recent elegant studies showing that sensitizing of insulin signaling by salicylates is induced via inhibition
of the activity of IκB kinase β (23–25). IL-1β is well known to activate the IκB kinase β and might thereby induce insulin resistance.

In conclusion, our data support the concept that subclinical activation of the immune system is involved in the pathogenesis
of type 2 diabetes. We demonstrated that a specific pattern of cytokines was associated with an increased risk of type 2 diabetes,
rather than isolated elevation of the respective cytokines.

Acknowledgments

This project was supported by grants from Gottfried-Wilhelm-Leibnitz-Gesellschaft. Further grants to the authors were from
the German Diabetes Association (104/03/2001 [to J.S. and M.M.] and 103/03/2001 [to M.R.]), Fritz-Thyssen-Stiftung (10.01.2.102),
Deutsche Forschungsgemeinschaft (RI 1076/1-1), the Eli-Lilly International Foundation (to J.S. and A.F.H.P.), the European
Union (SOC 95 201408 OSF02), and the Deutsche Krebshilfe (70-2488-HAI).

We thank K. Sprengel and S. Richter for laboratory assistance and U. Fiddicke and W. Bernigau for assistance with the study
data. The HbA1c analyses were conducted at the Department of Clinical Biochemistry, University of Greifswald, under the responsibility of
Dr. Hans-Joachim Rose. We thank C.A. Barth for critical discussion of the project.